
"""simple docstring"""



import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a       :						List[str]       		=		'''▁'''

a       :						Union[str, Any]       		=		{'''vocab_file''': '''spiece.model'''}

a       :						Optional[Any]       		=		{
    '''vocab_file''': {'''google/pegasus-xsum''': '''https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'''}
}

a       :						List[Any]       		=		{
    '''google/pegasus-xsum''': 5_1_2,
}


a       :						Dict       		=		logging.get_logger(__name__)




class 		a_    (			_UpperCAmelCase						):
    a   :					Tuple			     =					VOCAB_FILES_NAMES

    a   :					Optional[int]			     =					VOCAB_FILES_NAMES
    a   :					Tuple			     =					PRETRAINED_VOCAB_FILES_MAP
    a   :					str			     =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a   :					Any			     =					['input_ids', 'attention_mask']







    def __init__(      self      :							Optional[Any]  ,       __UpperCamelCase      :							Optional[int]  ,       __UpperCamelCase      :							List[str]="<pad>"  ,       __UpperCamelCase      :							Union[str, Any]="</s>"  ,       __UpperCamelCase      :							Dict="<unk>"  ,       __UpperCamelCase      :							Any="<mask_2>"  ,       __UpperCamelCase      :							Dict="<mask_1>"  ,       __UpperCamelCase      :							str=None  ,       __UpperCamelCase      :							Optional[Any]=1_03  ,       __UpperCamelCase      :							Optional[Dict[str, Any]] = None  ,       **__UpperCamelCase      :							Tuple  ,       )		->None:






        '''simple docstring'''






        _UpperCAmelCase        = offset
        if additional_special_tokens is not None:
            if not isinstance(__UpperCamelCase  ,       __UpperCamelCase  ):
                raise TypeError(
                    f"""additional_special_tokens should be of type {type(__UpperCamelCase  )}, but is"""
                    f""" {type(__UpperCamelCase  )}"""  )

            _UpperCAmelCase        = (
                ([mask_token_sent] + additional_special_tokens)
                if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
                else additional_special_tokens
            )
            # fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
            additional_special_tokens_extended += [
                f"""<unk_{i}>""" for i in range(len(__UpperCamelCase  )  ,       self.offset - 1  )
            ]

            if len(set(__UpperCamelCase  )  ) != len(__UpperCamelCase  ):
                raise ValueError(
                    """Please make sure that the provided additional_special_tokens do not contain an incorrectly"""
                    f""" shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}."""  )
            _UpperCAmelCase        = additional_special_tokens_extended
        else:
            _UpperCAmelCase        = [mask_token_sent] if mask_token_sent is not None else []
            additional_special_tokens += [f"""<unk_{i}>""" for i in range(2  ,       self.offset  )]

        _UpperCAmelCase        = {} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            eos_token=__UpperCamelCase  ,       unk_token=__UpperCamelCase  ,       mask_token=__UpperCamelCase  ,       pad_token=__UpperCamelCase  ,       mask_token_sent=__UpperCamelCase  ,       offset=__UpperCamelCase  ,       additional_special_tokens=__UpperCamelCase  ,       sp_model_kwargs=self.sp_model_kwargs  ,       **__UpperCamelCase  ,       )
        _UpperCAmelCase        = mask_token_sent
        _UpperCAmelCase        = vocab_file
        _UpperCAmelCase        = spm.SentencePieceProcessor(**self.sp_model_kwargs  )
        self.sp_model.Load(__UpperCamelCase  )

        # add special tokens to encoder dict
        _UpperCAmelCase        = {
            0: self.pad_token,
            1: self.eos_token,
        }

        if self.mask_token_sent is not None:
            self.encoder.update(
                {
                    2: self.mask_token_sent,
                    3: self.mask_token,
                }  )

        if self.offset > 0:
            # entries 2-104 are only used for pretraining and called <mask_1>, <mask_2>, unk_2, ...unk_102
            # mask_token_sent is already added to list -> so start at 1
            self.encoder.update({i + 3: additional_special_tokens[i] for i in range(1  ,       self.offset - 1  )}  )

        _UpperCAmelCase        = {v: k for k, v in self.encoder.items()}







    @property
    def   _snake_case       (      self      :							Optional[int]  )		->int:






        '''simple docstring'''






        return len(self.sp_model  ) + self.offset







    def   _snake_case       (      self      :							List[str]  )		->Dict[str, int]:






        '''simple docstring'''






        _UpperCAmelCase        = {self.convert_ids_to_tokens(__UpperCamelCase  ): i for i in range(self.vocab_size  )}
        vocab.update(self.added_tokens_encoder  )
        return vocab







    def __getstate__(      self      :							Any  )		->Union[str, Any]:






        '''simple docstring'''






        _UpperCAmelCase        = self.__dict__.copy()
        _UpperCAmelCase        = None
        return state







    def __setstate__(      self      :							Any  ,       __UpperCamelCase      :							Any  )		->List[str]:






        '''simple docstring'''






        _UpperCAmelCase        = d

        # for backward compatibility
        if not hasattr(self  ,       """sp_model_kwargs"""  ):
            _UpperCAmelCase        = {}

        _UpperCAmelCase        = spm.SentencePieceProcessor(**self.sp_model_kwargs  )
        self.sp_model.Load(self.vocab_file  )







    def   _snake_case       (      self      :							Optional[int]  ,       __UpperCamelCase      :							str  )		->List[str]:






        '''simple docstring'''






        return self.sp_model.encode(__UpperCamelCase  ,       out_type=__UpperCamelCase  )







    def   _snake_case       (      self      :							Any  ,       __UpperCamelCase      :							str  )		->int:






        '''simple docstring'''






        if token in self.decoder:
            return self.decoder[token]
        elif token in self.added_tokens_decoder:
            return self.added_tokens_decoder[token]
        _UpperCAmelCase        = self.sp_model.piece_to_id(__UpperCamelCase  )
        return sp_id + self.offset







    def   _snake_case       (      self      :							Optional[Any]  ,       __UpperCamelCase      :							int  )		->str:






        '''simple docstring'''






        if index in self.encoder:
            return self.encoder[index]
        elif index in self.added_tokens_encoder:
            return self.added_tokens_encoder[index]
        else:
            _UpperCAmelCase        = self.sp_model.IdToPiece(index - self.offset  )
        return token







    def   _snake_case       (      self      :							Any  ,       __UpperCamelCase      :							Dict  )		->int:






        '''simple docstring'''






        _UpperCAmelCase        = []
        _UpperCAmelCase        = """"""
        for token in tokens:
            # make sure that special tokens are not decoded using sentencepiece model
            if token in self.all_special_tokens:
                out_string += self.sp_model.decode(__UpperCamelCase  ) + token
                _UpperCAmelCase        = []
            else:
                current_sub_tokens.append(__UpperCamelCase  )
        out_string += self.sp_model.decode(__UpperCamelCase  )
        return out_string.strip()







    def   _snake_case       (      self      :							Dict  ,       __UpperCamelCase      :							Tuple=False  )		->int:






        '''simple docstring'''






        return 1







    def   _snake_case       (      self      :							Union[str, Any]  ,       __UpperCamelCase      :							int  )		->List[Any]:






        '''simple docstring'''






        _UpperCAmelCase        = set(self.all_special_ids  )  # call it once instead of inside list comp
        all_special_ids.remove(self.unk_token_id  )  # <unk> is only sometimes special

        return [1 if x in all_special_ids else 0 for x in seq]







    def   _snake_case       (      self      :							List[Any]  ,       __UpperCamelCase      :							List  ,       __UpperCamelCase      :							Optional[List] = None  ,       __UpperCamelCase      :							bool = False  )		->List[int]:






        '''simple docstring'''






        if already_has_special_tokens:
            return self._special_token_mask(__UpperCamelCase  )
        elif token_ids_a is None:
            return self._special_token_mask(__UpperCamelCase  ) + [1]
        else:
            return self._special_token_mask(token_ids_a + token_ids_a  ) + [1]







    def   _snake_case       (      self      :							int  ,       __UpperCamelCase      :							str  ,       __UpperCamelCase      :							Optional[Any]=None  )		->List[int]:






        '''simple docstring'''






        if token_ids_a is None:
            return token_ids_a + [self.eos_token_id]
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return token_ids_a + token_ids_a + [self.eos_token_id]







    def   _snake_case       (      self      :							Optional[int]  ,       __UpperCamelCase      :							str  ,       __UpperCamelCase      :							Optional[str] = None  )		->Tuple[str]:






        '''simple docstring'''






        if not os.path.isdir(__UpperCamelCase  ):
            logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""  )
            return
        _UpperCAmelCase        = os.path.join(
            __UpperCamelCase  ,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]  )

        if os.path.abspath(self.vocab_file  ) != os.path.abspath(__UpperCamelCase  ) and os.path.isfile(self.vocab_file  ):
            copyfile(self.vocab_file  ,       __UpperCamelCase  )
        elif not os.path.isfile(self.vocab_file  ):
            with open(__UpperCamelCase  ,       """wb"""  ) as fi:
                _UpperCAmelCase        = self.sp_model.serialized_model_proto()
                fi.write(__UpperCamelCase  )

        return (out_vocab_file,)

"""simple docstring"""



import math
import unittest


def 			_UpperCamelCase						(    _A   )     ->	bool:





    """simple docstring"""

    assert isinstance(_A       ,   _A   ) and (
        number >= 0
    ), "'number' must been an int and positive"

    if 1 < number < 4:
        # 2 and 3 are primes
        return True
    elif number < 2 or number % 2 == 0 or number % 3 == 0:
        # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
        return False

    # All primes number are in format of 6k +/- 1
    for i in range(5       ,   int(math.sqrt(_A   ) + 1   )       ,   6   ):
        if number % i == 0 or number % (i + 2) == 0:
            return False
    return True




class 		a_    (			unittest.TestCase						):







    def   _snake_case       (      self      :							int  )		->Optional[int]:






        '''simple docstring'''






        self.assertTrue(is_prime(2  )  )
        self.assertTrue(is_prime(3  )  )
        self.assertTrue(is_prime(5  )  )
        self.assertTrue(is_prime(7  )  )
        self.assertTrue(is_prime(11  )  )
        self.assertTrue(is_prime(13  )  )
        self.assertTrue(is_prime(17  )  )
        self.assertTrue(is_prime(19  )  )
        self.assertTrue(is_prime(23  )  )
        self.assertTrue(is_prime(29  )  )







    def   _snake_case       (      self      :							Union[str, Any]  )		->Optional[Any]:






        '''simple docstring'''






        with self.assertRaises(__UpperCamelCase  ):
            is_prime(-19  )
        self.assertFalse(
            is_prime(0  )  ,       """Zero doesn't have any positive factors, primes must have exactly two."""  ,       )
        self.assertFalse(
            is_prime(1  )  ,       """One only has 1 positive factor, primes must have exactly two."""  ,       )
        self.assertFalse(is_prime(2 * 2  )  )
        self.assertFalse(is_prime(2 * 3  )  )
        self.assertFalse(is_prime(3 * 3  )  )
        self.assertFalse(is_prime(3 * 5  )  )
        self.assertFalse(is_prime(3 * 5 * 7  )  )


if __name__ == "__main__":
 unittest.main()